THE APEX TIMES
Mike Hartnett at Bank of America argues that the debt of companies financing artificial intelligence could offer more value than parts of the crowded equity trade, pointing to how AI-focused firms are funding expansion.
Bank of America’s top strategist is urging investors to look beyond the most visible parts of the artificial intelligence boom and consider a less followed corner of the market: the bonds of technology companies using cash to fund AI build-outs.
In a note highlighted by Yahoo Finance, Bank of America strategist Hartnett characterized certain “tech bonds” as “diamonds in the rough,” suggesting that debt issued by companies tied to AI infrastructure may be mispriced relative to the market’s broader equity enthusiasm. The premise is that bond returns could benefit if AI hyperscalers continue funding growth in ways that alter capital-market behavior, even when the equity trade has already priced in much of the outlook.
The strategist’s argument, as summarized in the Yahoo Finance write-up, ties the bond opportunity to changes on the equity side of corporate finance. As AI-focused companies ramp up and issue more equity, the note suggests those same firms may also cut back on share buybacks. In the strategist’s framing, that combination can leave debt investors with a more favorable setup than equity investors expect.
The logic reflects a basic market dynamic: when companies shift how they allocate capital, the relative demand for different financial instruments can change. If buybacks slow, it can reduce the bid that equity investors provide under certain market conditions, while the cash flows supporting or refinancing corporate debt can still matter for bondholders. Hartnett’s “diamonds” metaphor implies that the bond market may not fully reflect those downstream effects.
Hartnett’s comments also reflect a more general reality that AI spending is not funded only through traditional research and development budgets. Data center construction, networking upgrades, and power procurement typically require large, recurring capital commitments. Companies often mix financing sources, and debt markets can become a key channel for spreading funding needs over time.
Still, the post does not lay out specific bond tickers, credit rating targets, yield levels, or which issuers the strategist has in mind. It also does not provide a detailed framework for how investors should screen or structure a “tech bond” portfolio. That limits what readers can conclude about the exact trade ideas, such as whether the emphasis is on investment-grade debt, high-yield bonds, specific maturities, or particular categories of AI suppliers.
For Bank of America, the note fits the bank’s broader role as a research shop that translates macro and corporate-finance trends into market positioning themes. It also comes as investors continue to treat AI-related equity performance as a central driver of sector sentiment, even as attention spreads to how companies actually pay for the build-out. In that environment, a call to examine the debt side can be seen as an attempt to diversify exposure within the same underlying technology growth story.
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